anthropics/knowledge-work-plugins

research-synthesis

Synthesize user research into themes, insights, and recommendations.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill research-synthesis

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

/research-synthesis

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Synthesize user research data into actionable insights. See the user-research skill for research methods, interview guides, and analysis frameworks.

Usage

/research-synthesis $ARGUMENTS

What I Accept

  • Interview transcripts or notes
  • Survey results (CSV, pasted data)
  • Usability test recordings or notes
  • Support tickets or feedback
  • NPS/CSAT responses
  • App store reviews

Output

markdown
## Research Synthesis: [Study Name]
**Method:** [Interviews / Survey / Usability Test] | **Participants:** [X]
**Date:** [Date range] | **Researcher:** [Name]

### Executive Summary
[3-4 sentence overview of key findings]

### Key Themes

#### Theme 1: [Name]
**Prevalence:** [X of Y participants]
**Summary:** [What this theme is about]
**Supporting Evidence:**
- "[Quote]" — P[X]
- "[Quote]" — P[X]
**Implication:** [What this means for the product]

#### Theme 2: [Name]
[Same format]

### Insights → Opportunities

| Insight | Opportunity | Impact | Effort |
|---------|-------------|--------|--------|
| [What we learned] | [What we could do] | High/Med/Low | High/Med/Low |

### User Segments Identified
| Segment | Characteristics | Needs | Size |
|---------|----------------|-------|------|
| [Name] | [Description] | [Key needs] | [Rough %] |

### Recommendations
1. **[High priority]** — [Why, based on which findings]
2. **[Medium priority]** — [Why]
3. **[Lower priority]** — [Why]

### Questions for Further Research
- [What we still don't know]

### Methodology Notes
[How the research was conducted, any limitations or biases to note]

If Connectors Available

If ~~user feedback is connected:

  • Pull support tickets, feature requests, and NPS responses to supplement research data
  • Cross-reference themes with real user complaints and requests

If ~~product analytics is connected:

  • Validate qualitative findings with usage data and behavioral metrics
  • Quantify the impact of identified pain points

If ~~knowledge base is connected:

  • Search for prior research studies and findings to compare against
  • Publish the synthesis to your research repository

Tips

  1. Include raw quotes — Direct participant quotes make insights credible and memorable.
  2. Separate observations from interpretations — "5 of 8 users clicked the wrong button" is an observation. "The button placement is confusing" is an interpretation.
  3. Quantify where possible — "Most users" is vague. "7 of 10 users" is specific.

Tâches connexes

du même dépôt

Autres Skills

Tous les Skills
anthropics
Officiel

testing-strategy

Design test strategies and test plans. Trigger with "how should we test", "test strategy for", "write tests for", "test plan", "what tests do we need", or when the user needs help with testing approaches, coverage, or test architecture.

Installations / 1h
1
GitHub Stars
34,2 k
Mis à jour
31 oct.
anthropics
Officiel

create-viz

Create publication-quality visualizations with Python. Use when turning query results or a DataFrame into a chart, selecting the right chart type for a trend or comparison, generating a plot for a report or presentation, or needing an interactive chart with hover and zoom.

Installations / 1h
4
GitHub Stars
33,8 k
Mis à jour
29 oct.
anthropics
Officiel

data-visualization

Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.

Installations / 1h
6
GitHub Stars
33,8 k
Mis à jour
29 oct.
anthropics
Officiel

brand-review

Review content against your brand voice, style guide, and messaging pillars, flagging deviations by severity with specific before/after fixes. Use when checking a draft before it ships, when auditing copy for voice consistency and terminology, or when screening for unsubstantiated claims, missing disclaimers, and other legal flags.

Installations / 1h
2
GitHub Stars
32,9 k
Mis à jour
24 oct.